“Natural language processing” generally refers to machine learning technology or other computing technology that supports interactions between humans and machines using natural language. Natural language processing often involves natural language understanding and natural language generation. Natural language understanding generally refers to technology allowing a machine to disassemble and parse communications that are input using natural language so that the machine can identify the proper meanings of the input communications. Natural language generation generally refers to technology allowing a machine to generate communications that are output using natural language so that the output communications have the proper meanings.
Recent work on natural language processing has often focused on semantic embedding of words into vector spaces, where relations between words are represented as vector differences in these spaces. Techniques for semantic embedding of words into vector spaces are typically based on the relationship between a word and the contexts in which the word appears. For example, existing techniques may use, as vector coordinates, the coefficients of a neural network that predicts nearby words from a given word or that predicts a given word from nearby words.